Abstract
This paper presents a retrospective of the benchmark testing methodologies developed and accumulated into the stretch sensor tool kit (SSTK) by the research team during the Closing the Wearable Gap series of studies. The techniques developed to validate stretchable soft robotic sensors (SRS) as a means for collecting human kinetic and kinematic data at the foot-ankle complex and at the wrist are reviewed. Lessons learned from past experiments are addressed, as well as what comprises the current SSTK based on what the researchers learned over the course of multiple studies. Three core components of the SSTK are featured: (a) material testing tools, (b) data analysis software, and (c) data collection devices. Results collected indicate that the stretch sensors are a viable means for predicting kinematic data based on the most recent gait analysis study conducted by the researchers (average root mean squared error or RMSE = 3.63°). With the aid of SSTK defined in this study summary and shared with the academic community on GitHub, researchers will be able to undergo more rigorous validation methodologies of SRS validation. A summary of the current state of the SSTK is detailed and includes insight into upcoming experiments that will utilize more sophisticated techniques for fatigue testing and gait analysis, utilizing SRS as the data collection solution.
Highlights
Feedback plays an important role in sports as real-time adjustments in training methods based on performance can help both coaches and athletes enhance output while mitigating the risk of injury [1].Electronics 2020, 9, 1457; doi:10.3390/electronics9091457 www.mdpi.com/journal/electronicsDue to the employment of varying training techniques used across multiple baselining and recovery philosophies, multiple sports, and varying levels of competition, ambiguity can arise in how to best develop and optimize the performance of an athlete
Origins of Closing the Wearable Gap Research In June 2017, a National Science Foundation (NSF) Innovation Corps (I-Corps) training site pilot grant funded an investigation on new athletic wearable technology
According to the responses from the I-Corps interviewees, there were trust concerns regarding the data from the wearable sensors due to consistent inaccuracies and lack of transparency regarding how correlations were being made
Summary
Feedback plays an important role in sports as real-time adjustments in training methods based on performance can help both coaches and athletes enhance output while mitigating the risk of injury [1]. Regardless of the programming paradigm, a central need for strength and conditioning (S&C) coaches is the ability to define performance improvements objectively [2]. For this reason, data collection has long been a part of the daily routine for S&C coaches. By using wearables to capture and examine performance data in near real-time, it is possible to provide the coach or athlete with immediate feedback, enabling coaches to adjust training programs such that they enhance workload output while mitigating the athlete’s future risk of injury [3]. Regardless of the tool and method used for data collection, the quality of the information is often the limiter for coaches looking to make genuinely informed decisions [4]
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